Specific power and efficiency of gasoline engines are influenced by factors such as compression ratio and Spark Advance (SA) regulation. These factors influence the combustion development over the crank angle: the trade-off between performance and the risk of irreversible damages is still a key element in the design of both high-performance (racing) and low-consumption engines.
This paper presents a novel approach to the problem, with the objective of defining a damage-related and operating conditions-independent index. The methodology is based on the combined analysis of indicating parameters, such as Cumulated Heat Release (CHR), Indicated Mean Effective Pressure (IMEP) and 50% Mass Fraction Burned (MFB50), and typical knock detection parameters, estimated by means of the in-cylinder pressure sensor signal.
Knocking combustions have several consequences, therefore they can be detected in many ways. As it is well known, knock excites the combustion chamber resonant frequencies, rising high frequency components in the in-cylinder pressure signal. Additionally, knocking combustions cause a higher heat flux through the combustion chamber walls, increasing the heat losses and lowering the IMEP: this effect can be observed by evaluating IMEP or CHR, that are based on the low-frequency content of the in-cylinder signal spectrum. A knock detection index can then be based on the crossed-observation of two phenomena, one set in the low-frequencies range and the other one on the high frequencies range of the in-cylinder pressure signal.
Knock-related parameters have been analyzed with a statistical approach, in order to define a detection strategy based on one single threshold value, to be used for all the engines, independently of engine speed and load: IMEP and CHR have been related to a typical high-frequency knock index, based on the Maximum Amplitude of Pressure Oscillations (MAPO) evaluated over the combustion angular window. It can be observed that, as knock intensity increases, the relationships between these parameters change. This change can be seized by evaluating the correlation coefficient between the parameters distributions and observing its trend as a function of SA (Spark Advance). The correlation coefficient is intrinsically normalized, therefore the index range is the same for every engine operating condition, and the paper shows that the threshold level, too, is constant. The same approach can be applied to determine SA corresponding to the best combustion phase, simply by evaluating the correlation coefficient for IMEP and MFB50 distributions.
The methodology has been successfully applied to different engines running in different speed and load conditions.